Bursts of Stellar Turbulence (Image 2)

A slide depicting a 3-D mixing layer between two fluids of different densities in a gravitational field. Known as a Rayleigh-Taylor instability--a type of turbulent mixing that occurs due to gravity, when a heavy gas is on top of a lighter one--this mixing plays an essential role in stellar convection and is being studied in this context to help devise and validate statistical models of turbulent fluid mixing at the boundaries of convection zones in stars. [Image 2 of 4 related images. See Image 3.]
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Paul Woodward and David Porter, astrophysicists at the University of Minnesota's Laboratory for Computational Science and Engineering (LCSE), are using the Pittsburgh Supercomputing Center's (PSC) Cray XT3 and PSC-developed software to run interactive simulations of turbulence.
The main focus of Woodward and Porter's research is astrophysical flows--specifically, using large-scale supercomputer simulations to understand and model turbulent convection in stars. Their long-term goal is to accurately simulate in detail, the turbulent dynamics of an entire giant star--stars similar to the sun. Woodward and Porter have been using small-scale turbulence to help identify parameters with which to build an accurate model of turbulence on a large scale.
It was their work on small-scale turbulence that led to a significant breakthrough when in January 2007, they used the entire system--4,096 XT3 processors (plus eight input/output nodes)--to simulate turbulent shear between two fluids. They used a computational grid of 5763 cells, fine enough to resolve the small-scale turbulence they wanted to understand--a run that would take weeks or months on an average cluster. With performance of 2.32 gigaflops (billions of calculations per second) on each XT3 processor, 9.5 teraflops overall, the run of 6,000 time steps was completed in 7.7 minutes.
To read more about this research, see "Bursts of Stellar Turbulence" from the PSC Projects in Scientific Computing 2007 Annual Report. [Numerical simulations were performed on the Cray XT3 at PSC and the visualization of the output data was performed at the LCSE on equipment purchased with support of National Science Foundation grants CNS 04-21423 and CNS 07-08822.] (Date of Image: 2007)
Credit: Prof. Paul Woodward, Laboratory for Computational Science and Engineering, University of Minnesota